Digital Texts II: Natural Language Processing and Deep Learning

Undergraduate / Graduate

This course is a theoretical and methodological introduction to advanced textual processing, understanding and analysis with a focus on current trends in deep learning and artificial intelligence. We will consider both the practical aspects of building AI models for language and the social, cultural, ethical and philosophical issues related to their development and deployment. In addition to evaluating these new methodologies in the light of traditional approaches, students will gain extensive experience in using Python to create and fine-tune deep learning and AI models, and by the end of the course will have developed their own individual projects, thereby gaining a practical understanding of advanced text analysis workflows along with specific tools and methods for evaluating models, systems and results. Prerequisite: DIGS 20031/30031 "Digital Texts I: Corpus Building and Corpus Statistics" or instructor consent.